Electrical impedance and image analysis methods in detecting and measuring Scots pine heartwood from a log end during tree harvesting

Scots pine (Pinus sylvestris L.) heartwood is naturally durable wood material which has not been fully utilized in the wood industry. Currently, there are no practical measurement methods for detecting and measuring heartwood in a tree harvesting. The objective of this study was to evaluate the applicability of an electrical impedance spectroscopy and an image analysis of a log end face for pine heartwood measurements from the harvesting perspective. Both methods were tested with a fresh wood material which was collected during the harvesting operations. The results indicate that both methods have potential to measure the heartwood from processed stems with an average heartwood diameter error being less than two centimeters for each method. However, the image analysis of the log end face is only appropriate when visible contrast between the heartwood and a sapwood exists. Our findings indicate that the studied heartwood detection methods show great potential in measuring the heartwood of the stem in the harvesting phase which would ideally benefit later links in wood value chains.Peer reviewe

Contribution of Common Genetic Variants to Risk of Early-Onset Ischemic Stroke

Background and Objectives Current genome-wide association studies of ischemic stroke have focused primarily on late-onset disease. As a complement to these studies, we sought to identify the contribution of common genetic variants to risk of early-onset ischemic stroke. Methods We performed a meta-analysis of genome-wide association studies of early-onset stroke (EOS), ages 18-59 years, using individual-level data or summary statistics in 16,730 cases and 599,237 nonstroke controls obtained across 48 different studies. We further compared effect sizes at associated loci between EOS and late-onset stroke (LOS) and compared polygenic risk scores (PRS) for venous thromboembolism (VTE) between EOS and LOS. Results We observed genome-wide significant associations of EOS with 2 variants in ABO, a known stroke locus. These variants tag blood subgroups O1 and A1, and the effect sizes of both variants were significantly larger in EOS compared with LOS. The odds ratio (OR) for rs529565, tagging O1, was 0.88 (95% confidence interval [CI]: 0.85-0.91) in EOS vs 0.96 (95% CI: 0.92-1.00) in LOS, and the OR for rs635634, tagging A1, was 1.16 (1.11-1.21) for EOS vs 1.05 (0.99-1.11) in LOS; p-values for interaction = 0.001 and 0.005, respectively. Using PRSs, we observed that greater genetic risk for VTE, another prothrombotic condition, was more strongly associated with EOS compared with LOS (p = 0.008). Discussion The ABO locus, genetically predicted blood group A, and higher genetic propensity for venous thrombosis are more strongly associated with EOS than with LOS, supporting a stronger role of prothrombotic factors in EOS.Peer reviewe

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Effect of steam treatment on the chemical composition of hemp (Cannabis sativa L.) and identification of the extracted carbohydrates and other compounds

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Classification of Wood Chips Using Electrical Impedance Spectroscopy and Machine Learning

Wood chips are extensively utilised as raw material for the pulp and bio-fuel industry, and advanced material analyses may improve the processes in utilizing these products. Electrical impedance spectroscopy (EIS) combined with machine learning was used in order to analyse heartwood content of pine chips and bark content of birch chips. A novel electrode system integrated in a sampling container was developed for the testing using frequency range 42 Hz&ndash;5 MHz. Three electrode pairs were used to measure the samples in x-, y- and z-direction. Three machine learning methods were used: K-nearest neighbor (KNN), decision tree (DT) and support vector machines (SVM). The heartwood content of pine chips and bark content of birch chips were classified with an accuracy of 91% using EIS from pure materials combined with a k-nearest neighbour classifier. When using mixed materials and multiple classes, 73% correct classification for pine heartwood content (four groups) and 64% for birch bark content (five groups) were achieved

A Comparative Study of Pyrolysis Liquids by Slow Pyrolysis of Industrial Hemp Leaves, Hurds and Roots

This study assessed the pyrolysis liquids obtained by slow pyrolysis of industrial hemp leaves, hurds, and roots. The liquids recovered between a pyrolysis temperature of 275–350 °C, at two condensation temperatures 130 °C and 70 °C, were analyzed. Aqueous and bio-oil pyrolysis liquids were produced and analyzed by proton nuclear magnetic resonance (NMR), gas chromatography–mass spectrometry (GC-MS), and atmospheric pressure photoionization Fourier transform ion cyclotron resonance mass spectrometry (APPI FT-ICR MS). NMR revealed quantitative concentrations of the most abundant compounds in the aqueous fractions and compound groups in the oily fractions. In the aqueous fractions, the concentration range of acetic acid was 50–241 gL−1, methanol 2–30 gL−1, propanoic acid 5–20 gL−1, and 1-hydroxybutan-2-one 2 gL−1. GC-MS was used to compare the compositions of the volatile compounds and APPI FT-ICR MS was utilized to determine the most abundant higher molecular weight compounds. The different obtained pyrolysis liquids (aqueous and oily) had various volatile and nonvolatile compounds such as acetic acid, 2,6-dimethoxyphenol, 2-methoxyphenol, and cannabidiol. This study provides a detailed understanding of the chemical composition of pyrolysis liquids from different parts of the industrial hemp plant and assesses their possible economic potential

Effects of two-year weather exposure on thermally modified Picea abies, Pinus sylvestris, and Fraxinus excelsior wood

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Pyrolysis distillates from tree bark and fibre hemp inhibit the growth of wood-decaying fungi

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